Paul Bernal
2020-May-07 05:53 UTC
[R] Working with very large datasets and generating an executable file
Dear Jeff, Thank you for the feedback. So, after reading your comments, it seems that, in order to develop an executable model that could be run in any OS, python might be the way to go then? I appreciate all of your valuable responses. Best regards, Paul El mi?., 6 de mayo de 2020 6:22 p. m., Jeff Newmiller < jdnewmil at dcn.davis.ca.us> escribi?:> Large data... yes, though how this can be done may vary. I have used > machines with 128G of RAM before with no special big data packages. > > Making an executable... theoretically, yes, though there are some > significant technical (and possibly legal) challenges that will most likely > make you question whether it was worth it if you try, particularly if your > intent is to obscure your code from the recipient. I (as a random user and > programmer on the Internet) would strongly discourage such efforts... it > will almost certainly be more practical to deliver code in script/package > form. > > On May 6, 2020 2:20:47 PM PDT, Paul Bernal <paulbernal07 at gmail.com> wrote: > >Dear R friends, > > > >Hope you are doing well. I have two questions, the first one is, can I > >work > >with very large datasets in R? That is, say I need to test several > >machine > >learning algorithms, like (random forest, multiple linear regression, > >etc.) > >on datasets having between 50 to 100 columns and 20 million > >observations, > >is there any way that R can handle data that large? > > > >The second question is, is there a way I can develop an R model and > >turn it > >into an executable program that can work on any OS? > > > >Any help and/or guidance will be greatly appreciated, > > > >Best regards, > > > >Paul > > > > [[alternative HTML version deleted]] > > > >______________________________________________ > >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >https://stat.ethz.ch/mailman/listinfo/r-help > >PLEASE do read the posting guide > >http://www.R-project.org/posting-guide.html > >and provide commented, minimal, self-contained, reproducible code. > > -- > Sent from my phone. Please excuse my brevity. >[[alternative HTML version deleted]]
Jeff Newmiller
2020-May-07 06:22 UTC
[R] Working with very large datasets and generating an executable file
There is no executable that can run on any OS. As for python... it is hardly the only game in town for building executables, but it and those other options are off topic here. On May 6, 2020 10:53:00 PM PDT, Paul Bernal <paulbernal07 at gmail.com> wrote:>Dear Jeff, > >Thank you for the feedback. So, after reading your comments, it seems >that, >in order to develop an executable model that could be run in any OS, >python >might be the way to go then? > >I appreciate all of your valuable responses. > >Best regards, > >Paul > >El mi?., 6 de mayo de 2020 6:22 p. m., Jeff Newmiller < >jdnewmil at dcn.davis.ca.us> escribi?: > >> Large data... yes, though how this can be done may vary. I have used >> machines with 128G of RAM before with no special big data packages. >> >> Making an executable... theoretically, yes, though there are some >> significant technical (and possibly legal) challenges that will most >likely >> make you question whether it was worth it if you try, particularly if >your >> intent is to obscure your code from the recipient. I (as a random >user and >> programmer on the Internet) would strongly discourage such efforts... >it >> will almost certainly be more practical to deliver code in >script/package >> form. >> >> On May 6, 2020 2:20:47 PM PDT, Paul Bernal <paulbernal07 at gmail.com> >wrote: >> >Dear R friends, >> > >> >Hope you are doing well. I have two questions, the first one is, can >I >> >work >> >with very large datasets in R? That is, say I need to test several >> >machine >> >learning algorithms, like (random forest, multiple linear >regression, >> >etc.) >> >on datasets having between 50 to 100 columns and 20 million >> >observations, >> >is there any way that R can handle data that large? >> > >> >The second question is, is there a way I can develop an R model and >> >turn it >> >into an executable program that can work on any OS? >> > >> >Any help and/or guidance will be greatly appreciated, >> > >> >Best regards, >> > >> >Paul >> > >> > [[alternative HTML version deleted]] >> > >> >______________________________________________ >> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >https://stat.ethz.ch/mailman/listinfo/r-help >> >PLEASE do read the posting guide >> >http://www.R-project.org/posting-guide.html >> >and provide commented, minimal, self-contained, reproducible code. >> >> -- >> Sent from my phone. Please excuse my brevity. >>-- Sent from my phone. Please excuse my brevity.
Paul Bernal
2020-May-07 06:39 UTC
[R] Working with very large datasets and generating an executable file
Dear Jeff, an executable in terms of deploying a machine learning model, whether it a classifocation, regression, time series or deep learning model. Best regards, Paul El jue., 7 de mayo de 2020 1:22 a. m., Jeff Newmiller < jdnewmil at dcn.davis.ca.us> escribi?:> There is no executable that can run on any OS. As for python... it is > hardly the only game in town for building executables, but it and those > other options are off topic here. > > On May 6, 2020 10:53:00 PM PDT, Paul Bernal <paulbernal07 at gmail.com> > wrote: > >Dear Jeff, > > > >Thank you for the feedback. So, after reading your comments, it seems > >that, > >in order to develop an executable model that could be run in any OS, > >python > >might be the way to go then? > > > >I appreciate all of your valuable responses. > > > >Best regards, > > > >Paul > > > >El mi?., 6 de mayo de 2020 6:22 p. m., Jeff Newmiller < > >jdnewmil at dcn.davis.ca.us> escribi?: > > > >> Large data... yes, though how this can be done may vary. I have used > >> machines with 128G of RAM before with no special big data packages. > >> > >> Making an executable... theoretically, yes, though there are some > >> significant technical (and possibly legal) challenges that will most > >likely > >> make you question whether it was worth it if you try, particularly if > >your > >> intent is to obscure your code from the recipient. I (as a random > >user and > >> programmer on the Internet) would strongly discourage such efforts... > >it > >> will almost certainly be more practical to deliver code in > >script/package > >> form. > >> > >> On May 6, 2020 2:20:47 PM PDT, Paul Bernal <paulbernal07 at gmail.com> > >wrote: > >> >Dear R friends, > >> > > >> >Hope you are doing well. I have two questions, the first one is, can > >I > >> >work > >> >with very large datasets in R? That is, say I need to test several > >> >machine > >> >learning algorithms, like (random forest, multiple linear > >regression, > >> >etc.) > >> >on datasets having between 50 to 100 columns and 20 million > >> >observations, > >> >is there any way that R can handle data that large? > >> > > >> >The second question is, is there a way I can develop an R model and > >> >turn it > >> >into an executable program that can work on any OS? > >> > > >> >Any help and/or guidance will be greatly appreciated, > >> > > >> >Best regards, > >> > > >> >Paul > >> > > >> > [[alternative HTML version deleted]] > >> > > >> >______________________________________________ > >> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >> >https://stat.ethz.ch/mailman/listinfo/r-help > >> >PLEASE do read the posting guide > >> >http://www.R-project.org/posting-guide.html > >> >and provide commented, minimal, self-contained, reproducible code. > >> > >> -- > >> Sent from my phone. Please excuse my brevity. > >> > > -- > Sent from my phone. Please excuse my brevity. >[[alternative HTML version deleted]]